Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques

Abdallah G. Motaal; Neamat El-Gayar; Nael F. Osman

doi:10.1007/978-3-642-12159-3_21

Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques

Abdallah G. Motaal, Neamat El-Gayar, Nael F. Osman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Different heart tissue identification is important for therapeutic decision-making in patients with myocardial infarction (MI), this provides physicians with a better clinical decision-making tool. Composite Strain Encoding (C-SENC) is an MRI acquisition technique that is used to acquire cardiac tissue viability and contractility images. It combines the use of blackblood delayed-enhancement (DE) imaging to identify the infracted (dead) tissue inside the heart muscle and the ability to image myocardial deformation from the strain-encoding (SENC) imaging technique. In this work, various machine learning techniques are applied to identify the different heart tissues and the background regions in the C-SENC images. The proposed methods are tested using numerical simulations of the heart C-SENC images and real images of patients. The results show that the applied techniques are able to identify the different components of the image with a high accuracy.

Original language	English (US)
Title of host publication	Artificial Neural Networks in Pattern Recognition - 4th IAPR TC3 Workshop, ANNPR 2010, Proceedings
Pages	231-240
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-12159-3_21
State	Published - 2010
Externally published	Yes
Event	4th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2010 - Cairo, Egypt Duration: Apr 11 2010 → Apr 13 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5998 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2010
Country/Territory	Egypt
City	Cairo
Period	4/11/10 → 4/13/10

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-12159-3_21

Cite this

Motaal, A. G., El-Gayar, N., & Osman, N. F. (2010). Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques. In Artificial Neural Networks in Pattern Recognition - 4th IAPR TC3 Workshop, ANNPR 2010, Proceedings (pp. 231-240). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5998 LNAI). https://doi.org/10.1007/978-3-642-12159-3_21

Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques. / Motaal, Abdallah G.; El-Gayar, Neamat; Osman, Nael F.
Artificial Neural Networks in Pattern Recognition - 4th IAPR TC3 Workshop, ANNPR 2010, Proceedings. 2010. p. 231-240 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5998 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Motaal, AG, El-Gayar, N & Osman, NF 2010, Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques. in Artificial Neural Networks in Pattern Recognition - 4th IAPR TC3 Workshop, ANNPR 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5998 LNAI, pp. 231-240, 4th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2010, Cairo, Egypt, 4/11/10. https://doi.org/10.1007/978-3-642-12159-3_21

Motaal AG, El-Gayar N, Osman NF. Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques. In Artificial Neural Networks in Pattern Recognition - 4th IAPR TC3 Workshop, ANNPR 2010, Proceedings. 2010. p. 231-240. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-12159-3_21

Motaal, Abdallah G. ; El-Gayar, Neamat ; Osman, Nael F. / Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques. Artificial Neural Networks in Pattern Recognition - 4th IAPR TC3 Workshop, ANNPR 2010, Proceedings. 2010. pp. 231-240 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques

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